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Robert is an empiricist who studies supply chains. He received his B.S. in Industrial Engineering, Operations Research from UC Berkeley in 2006, and his Ph.D. in Business Administration from the Stanford Graduate School of Business in 2012. He grew up in Palos Verdes, CA.

Areas of Expertise

EconometricsSupply Chain Design and Management

Education

PhD, 2012, Operations, Information, and Technology, Stanford Graduate School of Business, Stanford University

President/Social Chair, Stanford Graduate School of Business PhD Association, 2009-2011

Doctoral Fellowship, Stanford Graduate School of Business, 2007-12

Alumni Scholarship for Leadership, University of California at Berkeley, 2002-04

Articles

Bray, Robert and Haim Mendelson. Forthcoming. Production Smoothing and the Bullwhip Effect. Manufacturing & Service Operations Management (M&SOM).

The bullwhip effect and production smoothing appear antithetical because their empirical tests oppose one another: production variability exceeding sales variability for bullwhip, and vice versa for smoothing. But this is a false dichotomy. We distinguish between the phenomena with a new production smoothing measure, which estimates how much more variable production would be absent production volatility costs. We apply our metric to an automotive manufacturing sample comprising 162 car models and find 75% smooth production by at least 5%, despite 99% exhibiting the bullwhip effect. Indeed, we estimate both a strong bullwhip (on average, production is 220% as variable as sales) and robust smoothing (on average, production would be 22% more variable without deliberate stabilization). We find firms smooth both production variability and production uncertainty. We measure production smoothing with a structural econometric production scheduling model, based on the Generalized Order-Up-To Policy.

The bullwhip effect is the amplification of demand variability along a supply chain: a company bullwhips if it purchases from suppliers more variably than it sells to customers. Such bullwhips (amplifications of demand variability) can lead to mismatches between demand and production and hence to lower supply chain efficiency. We investigate the bullwhip effect in a sample of 4,689 public U.S. companies over 19742008. Overall, about two-thirds of firms bullwhip. The sample's mean and median bullwhips, both significantly positive, respectively, measure 15.8% and 6.7% of total demand variability. Put another way, the mean quarterly standard deviation of upstream orders exceeds that of demand by $20 million. We decompose the bullwhip by information transmission lead time. Estimating the bullwhip's information-lead-time components with a two-stage estimator, we find that demand signals firms observe with more than three quarters' notice drive 30% of the bullwhip, and those firms observe with less than one quarter's notice drive 51%. From 19741994 to 19952008, our sample's mean bullwhip dropped by a third.

We model how a judge schedules the cases in his docket as a multi-armed bandit problem. We show that the judge minimizes a case's expected ``duration"---its sojourn time minus its time to first hearing---when the hazard rate of case completion increases. We derive a multi-reservation scheduling heuristic (MRSH) that capitalizes on this insight: when a new case arrives, schedule several of its hearings up front, to cluster them in time. We apply our MRSH in an Italian labor court that exhibits increasing hazard rates. We estimate that our scheduling heuristic reduced the expected case flow time by 140 days (19%)

Operations Management (OPNS-430-0) 1Ys: This course is typically waived through the admissions process or the equivalent course Operations Management (Turbo) (OPNS-438A) was completed during the Summer term.
MMMs: This course is equivalent to the MMM core course Designing and Managing Business Processes (OPNS-440)
Operations management is the management of business processes--that is, the management of the recurring activities of a firm. This course aims to familiarize students with the problems and issues confronting operations managers, and to provide the language, concepts, insights and tools to deal with these issues to gain competitive advantage through operations. We examine how different business strategies require different business processes and how different operational capabilities allow and support different strategies to gain competitive advantage. A process view of operations is used to analyze different key operational dimensions such as capacity management, cycle time management, supply chain and logistics management, and quality management. Finally, we connect to recent developments such as lean or world-class manufacturing, just-in-time operations, time-based competition and business re-engineering.

Operations Management (Turbo) (OPNS-438-A) This accelerated course serves as an introduction to Operations Management. The course approaches the discipline from the perspective of the general manager, rather than from that of the operations specialist. The coverage is very selective: Students concentrate on a small list of powerful themes that have emerged recently as the central building blocks of world-class operations. The course also presents a sample of operations management tools and techniques that have proved extremely useful through the years. The topics discussed are equally relevant in the manufacturing and service sectors.

Operations Management (OPNSM-430-0)

Doctoral

Structural Estimation in Operations Management (OPNS-523-0) This seminar class covers structural estimation in operations management contexts---inventory management, supply chain coordination, service operations, facility positioning, and production scheduling. Each week, we study one or two papers in depth. Each paper presents both an economic model and an empirical means to estimate it; we focus on the empirical methodologies. There are weekly computer lab sessions covering the R programming language and several rigorous programming assignments.